As the FIFA tournament kicks off, researchers are showing their skills to help soccer coaches develop players and tactics.
What’s more interesting to coaches is information about events on the pitch and how players influenced them.
That’s also the kind of insight readily available to the naked eye of an experienced scout. But, Penn says, “the data is going to be less biased than someone’s opinion”. Ravi Ramineni worked as a data analyst at Microsoft before transferring in 2012 to a similar job at his local US Major League Soccer club, the Seattle Sounders in Washington. One of his first tasks was to use GPS data on how far the players ran, to optimize their training and preparation sessions. “Collecting this data during training, you can tell maybe today the training was too much or too little. You do that to try to prevent injuries.
“One thing you would hear in football analytics all the time is that we need to know what the player does off the ball,” says Ramineni. “For a specific incident in the match, the model can produce thousands of different simulations about what could have happened instead. So, you can start to say something about how well an attacking move went in that period of play.”
Karl Tuyls, a computer scientist at DeepMind, says the off-camera modelling work is the first step towards creating a virtual, AI-driven assistant coach that uses real-time data to guide decision-making in football and other sports. “You can imagine the AI looking at the first-half performance and suggesting a change in formation that might do better,” he says.
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